{"title":"Research on Optimal Allocation of Energy Storage in Distribution Network of Smart Park for Power-load Uncertainty","authors":"L. Xiang, Qian Dai, Junling Wu, Xing Tian, Xue Feng, Wenhe Peng","doi":"10.1145/3508297.3508320","DOIUrl":null,"url":null,"abstract":"This paper proposes an optimal allocation method of hybrid energy storage capacity with the goal of maximizing annual income aiming at coping cope with the adverse effects of randomness and volatility of photovoltaic power generation and electric vehicle charging on the distribution network of smart park. And the hybrid energy storage system consists of supercapacitors and lithium batteries. It can not only meet the demand for stabilizing power fluctuations, but also store electricity at low prices and sell electricity to the grid at high prices. A hybrid energy storage capacity allocation method based on time-of-use price is proposed, which allocates and optimizes the power and capacity of supercapacitors and lithium batteries respectively, and improves the income of hybrid energy storage system. Finally, the model is established, and the adaptive particle swarm algorithm (APSO) is used to verify the effectiveness of the method.","PeriodicalId":285741,"journal":{"name":"2021 4th International Conference on Electronics and Electrical Engineering Technology","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 4th International Conference on Electronics and Electrical Engineering Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3508297.3508320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes an optimal allocation method of hybrid energy storage capacity with the goal of maximizing annual income aiming at coping cope with the adverse effects of randomness and volatility of photovoltaic power generation and electric vehicle charging on the distribution network of smart park. And the hybrid energy storage system consists of supercapacitors and lithium batteries. It can not only meet the demand for stabilizing power fluctuations, but also store electricity at low prices and sell electricity to the grid at high prices. A hybrid energy storage capacity allocation method based on time-of-use price is proposed, which allocates and optimizes the power and capacity of supercapacitors and lithium batteries respectively, and improves the income of hybrid energy storage system. Finally, the model is established, and the adaptive particle swarm algorithm (APSO) is used to verify the effectiveness of the method.